Waste management methods and sustainablity

© Springer International Publishing Switzerland 2015. Waste in its different forms is a significant environmental issue that receives a great deal of attention worldwide. Waste is generated as a result of production and consumption (domestic and industrial) activities and tends to increase with the level of prosperity and economic development of the country. Cost efficient, technology-based and sustainable management of both solid and liquid waste is crucial to economic growth and development of a healthy society in any given region. This chapter reviews traditional as well as modern approaches to solid waste management (SWM) and wastewater treatment. Sustainable methods of waste reduction, waste reuse and recycling are the preferred options when managing waste. There are many environmental benefits that can be derived from the use of these methods. They reduce or prevent greenhouse gas emissions, lessen the release of pollutants, conserve resources, save energy and minimise the demand for waste treatment technology and space. Establishment of sanitary landfills that meet standard hygienic requirements is the most widely adopted method of disposing of solid waste in developed countries. Vermicomposting and biogas technology produce reusable manure and combustible gas respectively from organic solid waste while waste-to-energy (incineration of waste) has quickly emerged as one of the most attractive renewable energy options. Wastewater if not properly disposed of, could be hazardous to human health and environment. Natural aquatic and terrestrial treatment systems with the environment-friendly designs and low-cost sanitation provide benefits for the reuse of water. Wise uses of aquatic and terrestrial plants are a means of several natural wastewater treatment methods. A decentralized wastewater treatment is being considered for most communities because of its economic and environmental advantages. Apart from natural treatment methods, membrane technology, nanotechnology, microbial fuel cells and electrocoagulation offer newer approaches to handling wastewater in a sustainable manner. The overall sustainable development ensures the path of reconciliation for society, environment, and economy in the long-term. People who generate waste, institutions who handle it and the local governance are key partners in an efficient waste management system. Need for education to create awareness on the importance of waste treatment and the sustainability aspects of the emerging technologies remains critical at all societal and governmental levels. Applications of information and communication technologies offer ingenious solutions to the problem of waste management

Monitoring bacterial diversity in a full-scale municipal wastewater treatment plant in dubai by fluorescence in situ hybridization technique

In this study, the bacterial diversity in the activated sludge system of a full-scale municipal wastewater treatment plant in Dubai was monitored over a period of one year using ribosomal RNA (rRNA) targeted oligonucleotide probes for a defined phylogenetic group of bacteria by the Fluorescence in situ hybridization (FISH) technique. The largest fraction of the bacterial community in the sludge samples belonged to the gamma-subgroup of proteobacteria (25%) followed by gram positive bacteria of high G+C content(16%), gram positive bacteria with low G+C content (9 %), beta-proteobacteria (8%) and alpha-proteobacteria (5 %) with respect to the population percentages stained by DAPI (4,6-diamino-2-phenylindole). A specific nocardioform actinomycete, simultaneously targeted by both HGC69a and MNP1 probes, was predominantly found throughout the study period in all activated sludge mixed liquor samples. The nocardioform actinomycetes group members were detected in both branched and single cell morphotypes. Most of the previously published genus and species specific probes failed to hybridize to the sludge samples. In conclusion, the overall bacterial community populations detected by the sub-group specific 16S rRNA targeted oligonucleotide probes in FISH technique remained almost constant throughout the period of study irrespective of treatment plant conditions

Novel Fine-Tuned Attribute Weighted Na\"ive Bayes NLoS Classifier for UWB Positioning

In this paper, we propose a novel Fine-Tuned attribute Weighted Na\"ive Bayes (FT-WNB) classifier to identify the Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) for UltraWide Bandwidth (UWB) signals in an Indoor Positioning System (IPS). The FT-WNB classifier assigns each signal feature a specific weight and fine-tunes its probabilities to address the mismatch between the predicted and actual class. The performance of the FT-WNB classifier is compared with the state-of-the-art Machine Learning (ML) classifiers such as minimum Redundancy Maximum Relevance (mRMR)- $k$-Nearest Neighbour (KNN), Support Vector Machine (SVM), Decision Tree (DT), Na\"ive Bayes (NB), and Neural Network (NN). It is demonstrated that the proposed classifier outperforms other algorithms by achieving a high NLoS classification accuracy of $99.7\%$ with imbalanced data and $99.8\%$ with balanced data. The experimental results indicate that our proposed FT-WNB classifier significantly outperforms the existing state-of-the-art ML methods for LoS and NLoS signals in IPS in the considered scenario

Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distance dependent interference alignment (IA) approach for a generic 2-tier heterogeneous wireless network, where transmitters in the first and second tiers are distributed as Poisson Point Process (PPP) and Poisson Cluster Process (PCP) respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the trade-off between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared to statistical knowledge of distance. Furthermore, the remaining cross-tier and inter-cluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distance dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect

Transmit Antenna Selection for Massive MIMO Systems

In this paper, particle swarm optimization is employed to carry out transmit antenna subgrouping algorithm for massive multiple input and multiple output (MIMO) system. A minimum number of transmit antenna elements are selected to achieve a similar quality of service (QoS) as that of a single user MIMO system. Simulation results show that our proposed algorithm achieves similar capacity performance as compared to massive MIMO systems when employing exhaustive search for transmit antenna selection

Assessing methanogenic archaeal community in full scale anaerobic sludge digester systems in Dubai, United Arab Emirates

© 2018 Khan et al. Introduction: Anaerobic digestion for methane production comprises of an exceptionally diverse microbial consortium, a profound understanding about which is still constrained. In this study, the methanogenic archaeal communities in three full-scale anaerobic digesters of a Municipal Wastewater Treatment Plant were analyzed by Fluorescence in situ hybridization and quantitative real-time Polymerase Chain Reaction (qPCR) technique. Methods & Materials: Fluorescence in situ hybridization (FISH) was performed to detect and quantify the methanogenic Archaea in the sludge samples whereas qPCR was carried out to support the FISH analysis. Multiple probes targeting domain archaea, different orders and families of Archaea were used for the studies. Results and Discussion: In general, the aceticlastic organisms (Methanosarcinaceae & Methanosaetaceae) were more abundant than the hydrogenotrophic organisms (Methanobacteriales, Methanomicrobiales, Methanobacteriaceae & Methanococcales). Both FISH and qPCR indicated that family Methanosaetaceae was the most abundant suggesting that aceticlastic methanogenesis is probably the dominant methane production pathway in these digesters. Conclusion: Future work involving high-throughput sequencing methods and correlating archaeal communities with the main operational parameters of anaerobic digesters will help to obtain a better understanding of the dynamics of the methanogenic archaeal community in wastewater treatment plants in United Arab Emirates (UAE) which in turn would lead to improved performance of anaerobic sludge digesters

Bacterial community structure in anaerobic digesters of a full scale municipal wastewater treatment plant - Case study of dubai, united arab emirates

© 2019, International Centre for Sustainable Development of Energy, Water and Environment Systems SDEWES. All rights reserved. A highly complex microbial community involved in anaerobic sludge digesters plays vital roles in sludge treatment. The data on microbial ecology is important to accomplish efficient operation of the anaerobic digesters. This study is aimed at monitoring the bacterial community of three full-scale anaerobic digesters of a full-scale municipal wastewater treatment Plant in Dubai, United Arab Emirates. Fluorescent in-situ hybridization technique was applied to identify the bacterial groups and quantitative polymerase chain reaction to compare the richness of bacterial and archaeal domain. Results of the fluorescent in-situ hybridization technique analysis showed that the phylum Proteobacteria was most abundant followed by cytophage-Flavobacterium group of Bacteroides, Firmicutes and Actinobacteria. Among proteobacterial subclass Delta- and Alpha- were dominating than Gamma- and Beta-proteobacteria. The genus Desulfobacter and Desulfobacterium were the dominant groups hybridizing 70-76% of total 4\u27, 6\u27- diamidino - 2 phenylindole stained cells. The quantitative polymerase chain reaction results showed that Bacterial domain was dominating in all three digesters compared to the archaeal domain